Call Admission Control Scheme Research Articles

An intelligent load balancing algorithm for 5G‐satellite networks

SummaryCellular networks are projected to deal with an immense rise in data traffic, as well as an enormous and diverse device, plus advanced use cases, in the nearest future; hence, future 5G networks are being developed to consist of not only 5G but also different radio access technologies (RATs) integrated. In addition to 5G, the user's device (UD) will be able to connect to the network via LTE, WiMAX, WiFi, Satellite and other technologies. On the other hand, Satellite has been suggested as a preferred network to support 5G use cases. However, achieving load balancing is essential to guarantee an equal amount of traffic distributed between different RATs in a heterogeneous wireless network; this would enable optimal utilisation of the radio resources and lower the likelihood of call blocking/dropping. This study presented an artificial intelligent‐based application in heterogeneous wireless networks and proposed an enhanced particle optimisation (EPSO) algorithm to solve the load balancing problem in 5G‐Satellite networks. The algorithm uses a call admission control strategy to admit users into the network to ensure that users are evenly distributed on the network. The proposed algorithm was compared with the Artificial Bee Colony and Simulated Annealing algorithm using three performance metrics: throughput, call blocking and fairness. Finally, based on the experimental findings, results outcomes were analysed and discussed.

Performability analysis of multi-service call admission control schemes in LTE networks

Two important Quality-of-Service (QoS) measures for cellular networks are the fractions of New Calls (NCs) and Handoff Calls (HCs). These types of calls are usually blocked or dropped for two reasons: radio channels are occupied (performance reason) or failure of radio channels (availability reason). Call Admission Control (CAC) is a technique that accepts or rejects user requests in a network. This paper proposes two new CAC schemes for Long Term Evolution (LTE) networks supporting two classes of services (Real-Time (RT) and Non-Real-Time (NRT)). The proposed CAC schemes are composites, meaning that they consider performance changes associated with the failure and recovery of radio channels. We use the Probabilistic Model Checking (PMC) to perform a comparative analysis between the performability measures (combination of performance and availability measures) of the proposed composite CAC schemes and an existing pure performance model. First, we model the composite CAC schemes with multidimensional Continuous Time Markov Chain (CTMC). Then, we specify QoS requirements through the CTMC using the Continuous-time Stochastic Logic (CSL). Finally, we quantify the performability measures of the composite CAC schemes by checking CSL steady-state, transient, and path formulas using the PRISM model checker.

CO-CAC: A new approach to Call Admission Control for VoIP in 5G/WiFi UAV-based relay networks

Voice over IP (VoIP) requires a Call Admission Control (CAC) mechanism in WiFi networks to preserve VoIP packet flows from excessive network delay or packet loss. Ideally, this mechanism should be integrated with the operational scenario, guarantee the quality of service of active calls, and maximize the number of concurrent calls. This paper presents a novel CAC scheme for VoIP in the context of a WiFi access network deployed with Unmanned Aerial Vehicles (UAVs) that relay to a backhaul 5G network. Our system, named Codec-Optimization CAC (CO-CAC), is integrated into each drone. It intercepts VoIP call control messages and decides on the admission of every new call based on a prediction of the WiFi network’s congestion level and the minimum quality of service desired for VoIP calls. To maximize the number of concurrent calls, CO-CAC proactively optimizes the codec settings of active calls by exchanging signaling with VoIP users.We have simulated CO-CAC in a 50m × 50m scenario with four UAVs providing VoIP service to up to 200 ground users with IEEE 802.11ac WiFi terminals. Our results show that without CAC, the number of calls that did not meet a minimum quality level during the simulation was 10% and 90%, for 50 and 200 users, respectively. However, when CO-CAC was in place, all calls achieved minimum quality for up to 90 users without rejecting any call. For 200 users, only 25% of call attempts were rejected by the admission control scheme. These results were narrowly worse when the ground users moved randomly in the scenario.

Performance Evaluation of Call Admission Control Schemes in 3GPP Long Term Evolution Networks

Radio resource management (RRM) techniques are employed for resource utilization in wireless broadband networks. One of the major RRM techniques that are aimed at controlling the admission and rejection of new or handoff calls/connections in a network is known as Call Admission Control (CAC). CAC accepts or rejects a connection request based on a certain pre-determined criterion(s). Performance Evaluation of some existing CAC schemes was presented in this paper. The schemes evaluated are; Adaptive Call Admission Control Scheme with Bandwidth reservation termed as (ACAC), QoS-Aware Call Admission Control Scheme termed as (QA-CAC) and Enhanced Adaptive Call Admission Control Scheme with bandwidth reservation termed (EA-CAC). Vienna LTE system level simulator was used for the simulation experiments conducted. After several experiments, the results show that the QA-CAC and EA-CAC schemes perform better in terms of increasing the throughput of real-time (RT) traffic while all the three schemes almost have the same performance in terms of admitting the non-real-time (NRT) traffic.

Backoff Entropy: Predicting Presaturation Peak for IEEE 802.11 DCF Networks

In nonsaturated 802.11 distributed coordination function (DCF) networks, existing studies had observed a salient phenomenon: the maximum stable throughput may be far higher than the saturation throughput and last for a long duration (say, months). Such a maximum stable throughput is called the presaturation throughput peak. The long-duration peak suggests that 802.11 DCF networks may provide a far higher stable throughput than what we generally believe, without worrying about a sudden deterioration of quality of service (QoS). This paper is devoted to developing a general theoretical framework to predict the peak. In the framework, we define a backoff entropy to quantify the uncertainty of the inherent random backoff process of 802.11 DCF networks, and then innovatively introduce a BackoffEntropy-Peak linearity property (i.e., the peak is linearly proportional to the backoff entropy) for the peak prediction. This framework is applicable for a general configuration of contention windows (CWs). It enables us to reveal the most essential dependency of the peak on the initial CW size and the number of network nodes. Further, we design peak-based call admission control (CAC) schemes that can be performed quickly and easily, without requiring network performance measurements and complex calculations. We verify our framework and CAC schemes via widely adopted 802.11 DCF ns2 and ns3 simulators (mostly with typical 802.11 standard settings). Extensive simulations show that our framework and CAC schemes trade within 9% peak prediction errors for making 802.11 DCF networks provide high stable throughput with good QoS (such as short delay and low collision probability). This paper is the first to propose applying the information entropy to study the throughput-stability problem. We believe that this study makes a crucial breakthrough in thoroughly investigating nonsaturated performance and network stability of random access wireless networks.

A Review of Call Admission Control Schemes in Wireless Cellular Networks

A Review of Call Admission Control Schemes in Wireless Cellular Networks

Enhanced Adaptive Call Admission Control Scheme With Bandwidth Reservation for LTE Networks

Call admission control (CAC) is one of the radio resource management techniques that regulates and provide resources for new or ongoing calls in the network. The existing CAC schemes wastes bandwidth due to its failure to check before degrading admitted real-time calls and it also increases the call dropping probability (CBP) and calling blocking probability (CBP) of real-time calls due to the delay incurred when bandwidth is degraded from them. This paper proposed an enhanced adaptive call admission control (EA-CAC) scheme with bandwidth reservation. The scheme employs a prior-check mechanism that ensured bandwidth to be degraded will be enough to admit the new call request. It further incorporates an adaptive degradation mechanism that degrades non-real time calls before degrading the RT calls. The performance of the EA-CAC scheme was evaluated against two existing schemes using Vienna LTE system level simulator. The EA-CAC scheme exhibits better performance compared to the two schemes in terms of throughput, CBP, and CDP of RT calls without sacrificing the performance of NRT calls.

Study on call admission control schemes in 3GPP LTE network

Call admission control (CAC) is a process of accepting new calls or handoff calls in a network while regulating the Quality of Service (QoS) of existing or active calls without degrading any call drop. CAC is an RRM technique and directly impacts QoS for individual connection and the overall system efficiency. This paper presents a short review of some existing CAC schemes proposed for the 3GPP LTE network. The review aims to guide researchers to know what CAC is, how it operates, and its benefits to the overall system performance. The schemes reviewed can be classified based on the aim they were proposed, such as guaranteeing QoS of calls, increasing the utilization of available network resources, reducing call blocking, and call dropping probabilities. The paper further summarised all reviewed schemes by highlighting each scheme's operations, strengths, and weaknesses.

An optimum dynamic priority-based call admission control scheme for universal mobile telecommunications system

The dynamism associated with quality of service (QoS) requirement for traffic emanating from smarter end users devices founded on the internet of things (IoTs) drive, places a huge demand on modern telecommunication infrastructure. Most telecom networks, currently utilize robust call admission control (CAC) policies to ameliorate this challenge. However, the need for smarter CAC has becomes imperative owing to the sensitivity of traffic currently being supported. In this work, we developed a prioritized CAC algorithm for third Generation (3G) wireless cellular network. Based on the dynamic priority CAC (DP-CAC) model, we proposed an optimal dynamic priority CAC (ODP-CAC) scheme for Universal Mobile Telecommunication System (UMTS). We then carried out simulation under heavy traffic load while also exploiting renegotiation among different call traffic classes. Also, we introduced queuing techniques to enhance the new calls success probability while still maintaining a good handoff failure across the network. Results show that ODP-CAC provides an improved performance with regards to the probability of call drop for new calls, network load utilization and grade of service with average percentage value of 15.7%, 5.4% and 0.35% respectively.

Unified call admission control in corporate domains

Call Admission Control is a central mechanism for assurance of quality of service in telephony. While CAC is integrated into Public Switched Telephony Network (PSTN), its application to voice over IP in a corporate environment is challenging not only due to the heterogeneity of technologies, but also because of the difficulty of implementation into commercial VoIP terminals or Access Points.We present a novel framework that unifies call admission control for VoIP telephony corporate users despite their access network (i.e., WiFi or Ethernet) under a single corporate management domain. Our Unified CAC (U-CAC) system can be implemented in a VoIP Gateway/Proxy and uses only standard protocols already present in commercial off-the-shelf devices, avoiding the need to modify the firmware of existing APs or VoIP terminals. We define two variants of the decision algorithm: basic and advanced. In the basic mode of operation, the admission of new calls is based on the availability of spare circuits and the impact of the new call in the speech quality of VoWiFi calls in progress. In the advanced mode of operation, the traffic load in affected APs is proactively reduced by reconfiguring ongoing calls before rejecting the new call. Simulation results show that the number of simultaneous VoWiFi calls under guaranteed quality increases with our unified call admission control scheme. When using the advanced mode of operation, the number of simultaneous calls under guaranteed quality can be doubled when compared to the standard mode of operation.

Performance Evaluation of Dynamic QoS-Aware CAC (DQA-CAC) Algorithm for Broadband Networks

Call admission control (CAC) is a technique deployed in the management of network resources in mobile broadband networks. Despite its importance, the WiMAX technology like most mobile broadband networks does not make provision for CAC, making it an open area of research. A dynamic QoS-Aware Call Admission Control (DQACAC) scheme was recently proposed to improve resource utilization and ensure QoS. Several simulation experiments were conducted to evaluate the performance of the DQA-CAC against other CAC algorithms. The results of the simulation indicated that the DQA-CAC outperformed the existing CAC schemes in terms of reduced new connection blocking rate. However, the evaluation failed to consider other performance metrics like resource utilization and throughput that are also very crucial in the real-world scenario. This paper therefore attempts to improve the performance of the DQA-CAC by investigating its performance in terms of additional metrics like the average system throughput and resource utilization that further mimic the real-world experience. A Java based discrete event simulator designed for the study was used and the simulation results indicate that the DQA-CAC algorithm outperforms the existing CAC algorithms in terms of improved per-flow throughput, average system throughput and resource utilization in addition to reducing the connection blocking rate.

A Survey on Call Admission Control Schemes in LTE

A Survey on Call Admission Control Schemes in LTE

Neuro-Fuzzy based Call Admission Control for next Generation Mobile Multimedia Networks

As the demand of the mobile users are increasing day by day, wireless/mobile multimedia networks still need advancement in terms of, reliable traffic performance, link availability, efficient bandwidth utilization, and user mobility, that can attain extremely consistent wireless communication and data transmission over the networks. Due to the emerging demand of multimedia services a high-speed network and call admission control (CAC) scheme is required, which not only guarantees the quality of services (QoS) for new and handoff calls but also results in optimum resource utilization in bursty traffic network environments. The main objective of this integrated neural fuzzy based CAC scheme is to improve QoS with decent resource allocation, such that it minimizes the probability of call dropping and call blocking in mobile multimedia networks. The proposed neural fuzzy CAC scheme is a hybrid approach that integrates the semantic rule ability of fuzzy logic (FL) controller and self-training capability of a neural network (NN) which is further enhanced to construct an efficient computational model for traffic control and fair radio resources allocation for new calls and handoff calls. The simulation results conclude that a neural fuzzy based CAC can achieve minimal call dropping probabilities and maximum resource utilization in high-speed networks as compared to fuzzy logic based CAC and conventional CAC or existing CAC schemes

Fuzzy-based decisive approach for call admission control in the LTE networks

Long term evolution (LTE) is a user-friendly network in providing a user requested service, and the growth of LTE is reported exponentially due to the attractive applications. The existence of the huge number of users and a massive presence of user demands in the network raise a question on the Quality-of-Service (QoS). In order to assure the required QoS with the available resources in the network, the paper proposes a call admission control scheme using a fuzzy-based decisive approach. The proposed method works based on the available resources in the network and allocates extra resource blocks when there is a lag in the demanded QoS. The flexible and user-friendly service is assured to three groups of users, for which the users are categorized based on the requested service as soon the service is requested. The simulation environment is developed to perform the fuzzy-based call admission control in LTE such that the results prove that the proposed method outperformed the existing methods in terms of delay, throughput, cell power, and call drops. The delay, throughput, cell power, and call drops using the proposed method are 0.1103 s, 1,294,932 bps, 44.2071 dBm, and 328, respectively. Also, the proposed method has the minimum call blocking probability of 0.0527 and 0.2901 for handoff users and new users. It has the call dropping probability of 0.0528 and 0.3357 for handoff users and new users, respectively.

A Hybrid Approach to Call Admission Control in 5G Networks

Artificial intelligence is employed for solving complex scientific, technical, and practical problems. Such artificial intelligence techniques as neural networks, fuzzy systems, and genetic and evolutionary algorithms are widely used for communication systems management, optimization, and prediction. Artificial intelligence approach provides optimized results in a challenging task of call admission control, handover, routing, and traffic prediction in cellular networks. 5G mobile communications are designed as heterogeneous networks, whose important requirement is accommodating great numbers of users and the quality of service satisfaction. Call admission control plays a significant role in providing the desired quality of service. An effective call admission control algorithm is needed for optimizing the cellular network system. Many call admission control schemes have been proposed. The paper proposes a methodology for developing a genetic neurofuzzy controller for call admission in 5G networks. Performance of the proposed admission control is evaluated through computer simulation.

Channel Allocation Scheme for Cellular Network Using Fuzzy Logic

This paper, deals fuzzy call admission control scheme to the requirement of quality of service. Quality of service is very critical issue in mobile communication because of dearth of spectrum resource and mobility of consumer and the main parameter is call dropping probable condition which shows the possibility of the extant relation being refusable during mobility. When the consumer’s call suddenly abolished in the term of the connection is more troubling than being obstructed likely on a new call try. Performance of channel allocation scheme is evaluated, using fuzzy control in terms of call dropping probability and channel utilization

Fuzzy logic-based call admission control in 5G cloud radio access networks with preemption

Fifth generation (5G) cellular networks will be comprised of millions of connected devices like wearable devices, Androids, iPhones, tablets, and the Internet of Things (IoT) with a plethora of applications generating requests to the network. The 5G cellular networks need to cope with such sky-rocketing traffic requests from these devices to avoid network congestion. As such, cloud radio access networks (C-RAN) has been considered as a paradigm shift for 5G in which requests from mobile devices are processed in the cloud with shared baseband processing. Despite call admission control (CAC) being one of radio resource management techniques to avoid the network congestion, it has recently been overlooked by the community. The CAC technique in 5G C-RAN has a direct impact on the quality of service (QoS) for individual connections and overall system efficiency. In this paper, a novel fuzzy logic-based CAC scheme with preemption in C-RAN is proposed. In this scheme, cloud bursting technique is proposed to be used during congestion, where some delay tolerant low-priority connections are preempted and outsourced to a public cloud with a penalty charge. Simulation results show that the proposed scheme has low blocking probability below 5%, high throughput, low energy consumption, and up to 95% of return on revenue.

An Adaptive Call Admission Control Scheme for Overflowed Traffic with Buffering of Data/New Voice Calls in Multilayer 3G Wireless Mobile Networks

An Adaptive Call Admission Control Scheme for Overflowed Traffic with Buffering of Data/New Voice Calls in Multilayer 3G Wireless Mobile Networks

An Adaptive Call Admission Control With Bandwidth Reservation for Downlink LTE Networks

In recent years, consumers of 4G cellular networks have increased exponentially as they discover that the service is user-friendly. Due to the large users and their frequent demands, it is necessary to use the limited network resources that guarantee the eminent standard quality of service (QoS). Call admission control (CAC) scheme has a major impact in assuring QoS for different users with various QoS requirements in 4G networks. Recently, the reservation-based scheme and bandwidth degradation schemes were proposed with the aim to provide effective use of network resources and assure QoS requirements to admitted calls. However, in spite of these several objectives, these schemes are not efficient as a result of the modeling and approximation method that starve the best effort (BE) traffic. The dynamic threshold value approach adjusts handoff call and new call based on time-varying conditions resulted in a waste of network resources, where bandwidth are reserved for handoff call, but at the network environment, there is little or no handoff calls. In this paper, we propose a novel CAC scheme to provide effective use of network resources and avoid the starvation of BE traffic. The scheme introduces an adaptive threshold value, which adjusts the network resources under heavy traffic intensity. In addition, we proposed reservation and degradation approach to admit many users when there is a limited number of bandwidth, which also achieved effective utilization of network resources. Simulation results show that the proposed scheme significantly outperforms the reservation-based scheme and bandwidth degradation schemes in terms of admitting many calls and guaranteeing QoS to all the traffic types in the network. Numerical results imitate to experimental results with insignificant differences.

A Reinforcement Learning Approach to Call Admission Control in HAPS Communication System

The large changing of link capacity and number of users caused by the movement of both platform and users in communication system based on high altitude platform station (HAPS) will resulting in high dropping rate of handover and reduce resource utilization. In order to solve these problems, this paper proposes an adaptive call admission control strategy based on reinforcement learning approach. The goal of this strategy is to maximize long-term gains of system, with the introduction of cross-layer interaction and the service downgraded. In order to access different traffics adaptively, the access utility of handover traffics and new call traffics is designed in different state of communication system. Numerical simulation result shows that the proposed call admission control strategy can enhance bandwidth resource utilization and the performances of handover traffics.